Machine learning approaches for population health analytics through social media

Machine Learning Approaches for Population Health Analytics through Social Media by Dinh Hung Nguyen MSc.Eng Submitted in fulfilment of the requirements for the degree of Doctor of Philosophy Deakin University April 2020 DEAKIN UNIVERSITY ACCESS TO THESIS - A I am the author of the thesis entitled Machine Learning Approaches for Population Health Analytics through Social Media submitted for the degree of Doctor of Philosophy This thesis may be made available for consultation, loan and limited copying in accordance with the Copyright Act 1968 'I certify that I am the student named below and that the information provided in the form is correct' Full Name: Dinh Hung Nguyen Signed: Date: 14/9/2020 DEAKIN UNIVERSITY CANDIDATE DECLARATION I certify the following about the thesis entitled Machine Learning Approaches for Population Health Analytics through Social Media submitted for the degree of Doctor of Philosophy a I am the creator of all or part of the whole work(s) (including content and layout) and that where reference is made to the work of others, due acknowledgment is given b The work(s) are not in any way a violation or infringement of any copyright, trademark, patent, or other rights whatsoever of any person c That if the work(s) have been commissioned, sponsored or supported by any organisation, I have fulfilled all of the obligations required by such contract or agreement d That any material in the thesis which has been accepted for a degree or diploma by any university or institution is identified in the text e All research integrity requirements have been complied with 'I certify that I am the student named below and that the information provided in the form is correct' Full Name: DINH HUNG NGUYEN Signed: Date: 27/04/2020 Deakin University CRICOS Provider Code 00113B Acknowledgments This thesis would not have been possible without the support, guidance and encouragement of many people First, I would like to express my sincere gratitude to my supervisors, Dr Thin Nguyen and Dr Duc Thanh Nguyen, for their professional guidance, valuable comments, practical suggestions, constructive criticism and continuous encouragement throughout my studies I would like to extend my deep thanks to Prof Dinh Phung and Prof Svetha Venkatesh for giving me the opportunity to pursue a PhD at the A2I2, a leading artificial intelligence research institute in Australia I am deeply grateful to the Ministry of Education and Training of Vietnam, Nha Trang University and Deakin University for granting me time and financial support I would like to thank Dr Bo Dao, Dr Tu Nguyen and Dr Hung Vu, for their help and encouragement during my early days at Deakin My sincere thanks go to all researchers and staff at A2I2 for their support, cooperation and kindness Finally, this thesis is dedicated to my family I am forever indebted to my late parents, Phung and Duong, for their love and effort in raising me to be a better individual I deeply thank my parents-in-law, Sung and Thanh, for their support through my long journey I especially thank my son and daughter, Hoang and Mai Anh, for giving me unlimited happiness and pleasure Most of all, I would like to express special thanks to my beloved wife, Hang, for her unconditional love, silent sacrifice and constant encouragement during my hard times i Contents Acknowledgments i Abstract x Relevant Publications xii Introduction 1.1 Background and Aims 1.2 Contributions 1.3 Thesis Structure Literature Review 2.1 An Overview of Social Media 2.2 Social Media and Health Care 2.2.1 Health Communication 2.2.2 Public Health Surveillance 10 2.2.3 Health Promotion 11 ii 2.3 2.2.4 Medical Intervention 11 2.2.5 Medical Science and Education 12 2.2.6 Social Media for Health Analytics 12 Social Media Data Types for Population Health Analytics 13 2.3.1 2.3.2 Textual Data 13 2.3.1.1 Psycholinguistic Features 14 2.3.1.2 Latent Topics 15 Visual Data 16 2.3.2.1 Low-level Features 16 2.3.2.2 Semantic Objects 18 2.3.2.3 Learned Features Using Deep Learning 19 2.3.3 Spatio-temporal Data 20 2.3.4 Digital Social Capital 21 2.4 Population-scale Health Representations 22 2.5 Health Index Estimation 23 Content-based Population Representations 26 3.1 Motivation 26 3.2 Statistical Representations 27 3.2.1 Independent Statistical Representations iii 27 3.2.2 Dependent Statistical Representations 28 3.2.3 Experiments 29 3.2.4 3.3 Dataset 29 3.2.3.2 Experimental Setup 30 Results 31 Distance Representations 33 3.3.1 Set Probabilistic Distance Representations 33 3.3.2 Experiments 3.3.3 3.4 3.2.3.1 35 3.3.2.1 Data 35 3.3.2.2 Experimental Setup 35 Results 36 Conclusion 37 Interaction-based Population Representations 38 4.1 Motivation 38 4.2 Proposed Approach 39 4.2.1 4.2.2 Graph Construction 39 4.2.1.1 Inter-feature Graph 40 4.2.1.2 Inter-tweet Graph 40 Graph-based Population Representation 41 iv 4.3 4.2.2.1 Graph Properties 42 4.2.2.2 Graph Kernels 43 Experiments 44 4.3.1 Case Studies 44 4.3.1.1 Case Study Population Health Index Estimation 45 4.3.1.2 Case Study Population Health Situation Classification 45 4.3.2 4.4 4.5 Dataset 45 Results 46 4.4.1 Case study Population Health Index Estimation 46 4.4.2 Case study 2: Population Health Status Classification 49 Conclusion 53 Multi-domain Social Media Data for Health Analytics 54 5.1 Motivation 54 5.2 Study Design 56 5.2.1 Participants, Recruitment and Procedure 56 5.2.2 Measures 5.2.3 Social Media Data Collection and Analysis 57 56 5.3 Proposed Network Architecture 57 5.4 Experiments 60 v 5.5 5.6 5.4.1 Data 60 5.4.2 Experimental Setup 61 Results 62 5.5.1 Estimation of Mental Health Scores 62 5.5.2 Estimation of Affective Scores 64 5.5.3 Joint Network v Separate Networks 65 Conclusion 66 Conclusion 67 6.1 Summary 67 6.2 Future Directions 68 Bibliography 70 vi List of Figures 2.1 An example of a mental health-related Twitter message Retrieved 12 April 2020 14 2.2 Examples of Flickr photographs with associated text Retrieved 03 November 2017 Best viewed 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We would like to hear from you E-mail us at customercare@copyright.com https://s100.copyright.com/AppDispatchServlet#formTop CLOSE | Terms and Conditions 1/1 27/02/2020 Rightslink® by Copyright Clearance Center RightsLink Home Help Email Support Dinh Hung Nguyen SPDF: Set Probabilistic Distance Features for Prediction of Population Health Outcomes via Social Media Author: Hung Nguyen, Duc Thanh Nguyen, Thin Nguyen Publication: Springer eBook Publisher: Springer Nature Date: Jan 1, 2019 Copyright © 2019, Springer Nature Singapore Pte Ltd Order Completed Thank you for your order This Agreement between Mr Hung Nguyen ("You") and Springer Nature ("Springer Nature") consists of your license details and the terms and conditions provided by Springer Nature and Copyright Clearance Center Your rmation email will contain your order number for future reference License Number 4776701429962 License date Feb 26, 2020 Licensed Content Order Details Licensed Content Publisher Springer Nature Licensed Content Publication Springer eBook Licensed Content Title SPDF: Set Probabilistic Distance Features for Prediction of Population Health Outcomes via Social Media Licensed Content Author Hung Nguyen, Duc Thanh Nguyen, Thin Nguyen Licensed Content Date Jan 1, 2019 About Your Work Type of Use Thesis/Dissertation Requestor type academic/university or research institute Format print and electronic Portion full article/chapter Will you be translating? no Circulation/distribution - 29 Author of this Springer Nature content yes Additional Data Title Machine Learning Approaches for Health Analytics through Social Media Institution name Deakin University Expected presentation date Apr 2020 Requestor Location Requestor Location Printable Details Tax Details Mr Hung Nguyen A2I2, Deakin University, KA Building 75 Pigdons Road, Waurn Ponds Waurn Ponds, Victoria 3216 Australia Attn: Mr Hung Nguyen Price Total https://s100.copyright.com/AppDispatchServlet 0.00 AUD 1/2 27/02/2020 Rightslink® by Copyright Clearance Center RightsLink Home Help Email Support Dinh Hung Nguyen Estimating Support Scores of Autism Communities in LargeScale Web Information Systems Author: Nguyen Thin, Nguyen Hung, Svetha Venkatesh et al Publication: Springer eBook Publisher: Springer Nature Date: Jan 1, 2017 Copyright © 2017, Springer International Publishing AG Order Completed Thank you for your order This Agreement between Mr Hung Nguyen ("You") and Springer Nature ("Springer Nature") consists of your license details and the terms and conditions provided by Springer Nature and Copyright Clearance Center Your rmation email will contain your order number for future reference License Number 4776711242010 License date Feb 26, 2020 Licensed Content Order Details Licensed Content Publisher Springer Nature Licensed Content Publication Springer eBook Licensed Content Title Estimating Support Scores of Autism Communities in Large-Scale Web Information Systems Licensed Content Author Nguyen Thin, Nguyen Hung, Svetha Venkatesh et al Licensed Content Date Jan 1, 2017 About Your Work Type of Use Thesis/Dissertation Requestor type academic/university or research institute Format print and electronic Portion full article/chapter Will you be translating? no Circulation/distribution - 29 Author of this Springer Nature content yes Additional Data Title Machine Learning Approaches for Health Analytics through Social Media Institution name Deakin University Expected presentation date Apr 2020 Requestor Location Requestor Location Printable Details Tax Details Mr Hung Nguyen A2I2, Deakin University, KA Building 75 Pigdons Road, Waurn Ponds Waurn Ponds, Victoria 3216 Australia Attn: Mr Hung Nguyen Price Total 0.00 AUD Total: 0.00 AUD https://s100.copyright.com/AppDispatchServlet 1/2 27/02/2020 Rightslink® by Copyright Clearance Center RightsLink Home Help Email Support Dinh Hung Nguyen Using spatiotemporal distribution of geocoded Twitter data to predict US county-level health indices Author: Thin Nguyen,Mark Larsen,Bridianne O’Dea,Hung Nguyen,Duc Thanh Nguyen,John Yearwood,Dinh Phung,Svetha Venkatesh,Helen Christensen Publication: Future Generation Computer Systems Publisher: Elsevier Date: Available online 17 January 2018 © 2018 Elsevier B.V All rights reserved Please note that, as the author of this Elsevier article, you retain the right to include it in a thesis or dissertation, provided it is not published commercially.  Permission is not required, but please ensure that you reference the journal as the original source.  For more information on this and on your other retained rights, please visit: https://www.elsevier.com/about/our-business/policies/copyright#Author-rights BACK © 2020 Copyright - All Rights Reserved | Copyright Clearance Center, Inc | Privacy statement Comments? We would like to hear from you E-mail us at customercare@copyright.com https://s100.copyright.com/AppDispatchServlet CLOSE WINDOW | Terms and Conditions 1/1 27/02/2020 Rightslink® by Copyright Clearance Center RightsLink Home Help Email Support Dinh Hung Nguyen Estimating County Health Indices Using Graph Neural Networks Author: Hung Nguyen, Duc Thanh Nguyen, Thin Nguyen Publication: Springer eBook Publisher: Springer Nature Date: Jan 1, 2019 Copyright © 2019, Springer Nature Singapore Pte Ltd Order Completed Thank you for your order This Agreement between Mr Hung Nguyen ("You") and Springer Nature ("Springer Nature") consists of your license details and the terms and conditions provided by Springer Nature and Copyright Clearance Center Your rmation email will contain your order number for future reference License Number 4776701067019 License date Feb 26, 2020 Licensed Content Order Details Licensed Content Publisher Springer Nature Licensed Content Publication Springer eBook Licensed Content Title Estimating County Health Indices Using Graph Neural Networks Licensed Content Author Hung Nguyen, Duc Thanh Nguyen, Thin Nguyen Licensed Content Date Jan 1, 2019 About Your Work Type of Use Thesis/Dissertation Requestor type academic/university or research institute Format print and electronic Portion full article/chapter Will you be translating? no Circulation/distribution - 29 Author of this Springer Nature content yes Additional Data Title Machine Learning Approaches for Health Analytics through Social Media Institution name Deakin University Expected presentation date Apr 2020 Requestor Location Requestor Location Printable Details Tax Details Mr Hung Nguyen A2I2, Deakin University, KA Building 75 Pigdons Road, Waurn Ponds Waurn Ponds, Victoria 3216 Australia Attn: Mr Hung Nguyen Price Total 0.00 AUD Total: 0.00 AUD https://s100.copyright.com/AppDispatchServlet 1/2 27/02/2020 Rightslink® by Copyright Clearance Center RightsLink Home Help Email Support Dinh Hung Nguyen Jointly Predicting A ective and Mental Health Scores Using Deep Neural Networks of Visual Cues on the Web Author: Hung Nguyen, Van Nguyen, Thin Nguyen et al Publication: Springer eBook Publisher: Springer Nature Date: Jan 1, 2018 Copyright © 2018, Springer Nature Switzerland AG Order Completed Thank you for your order This Agreement between Mr Hung Nguyen ("You") and Springer Nature ("Springer Nature") consists of your license details and the terms and conditions provided by Springer Nature and Copyright Clearance Center Your rmation email will contain your order number for future reference License Number 4776710116277 License date Feb 26, 2020 Licensed Content Order Details Licensed Content Publisher Springer Nature Licensed Content Publication Springer eBook Licensed Content Title Jointly Predicting A ective and Mental Health Scores Using Deep Neural Networks of Visual Cues on the Web Licensed Content Author Hung Nguyen, Van Nguyen, Thin Nguyen et al Licensed Content Date Jan 1, 2018 About Your Work Type of Use Thesis/Dissertation Requestor type academic/university or research institute Format print and electronic Portion full article/chapter Will you be translating? no Circulation/distribution - 29 Author of this Springer Nature content yes Additional Data Title Machine Learning Approaches for Health Analytics through Social Media Institution name Deakin University Expected presentation date Apr 2020 Requestor Location Requestor Location Printable Details Tax Details Mr Hung Nguyen A2I2, Deakin University, KA Building 75 Pigdons Road, Waurn Ponds Waurn Ponds, Victoria 3216 Australia Attn: Mr Hung Nguyen Price Total 0.00 AUD Total: 0.00 AUD https://s100.copyright.com/AppDispatchServlet 1/2 ... thesis entitled Machine Learning Approaches for Population Health Analytics through Social Media submitted for the degree of Doctor of Philosophy This thesis may be made available for consultation,... field of population health analytics through social media using machine learning methods Specifically, we develop various machine learning models to estimate the health indices and classify health. .. use of social media for healthcare, especially for public healthcare We then review common social media data types used in health analytics, including text, images, spatiotemporal data and social